Surface Registration by Optimization in Constrained Diffeomorphism Space

Wei Zeng Florida International University Ronald Lok Ming Lui The Chinese University of Hong Kong Xianfeng Gu Stony Brook University

Computational Geometry mathscidoc:1609.09017

IEEE Conference on Computer Visions and Pattern Recognition, 4169-4176, 2014.9
This work proposes a novel framework for optimization in the constrained diffeomorphism space for deformable surface registration. First the diffeomorphism space is modeled as a special complex functional space on the source surface, the Beltrami coefficient space. The physically plausible constraints, in terms of feature landmarks and deformation types, define subspaces in the Beltrami coefficient space. Then the harmonic energy of the registration is minimized in the constrained subspaces. The minimization is achieved by alternating two steps: 1) optimization - diffuse the Beltrami coefficient, and 2) projection - first deform the conformal structure by the current Beltrami coefficient and then compose with a harmonic map from the deformed conformal structure to the target. The registration result is diffeomorphic, satisfies the physical landmark and deformation constraints, and minimizes the conformality distortion. Experiments on human facial surfaces demonstrate the efficiency and efficacy of the proposed registration framework.
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@inproceedings{wei2014surface,
  title={Surface Registration by Optimization in Constrained Diffeomorphism Space},
  author={Wei Zeng, Ronald Lok Ming Lui, and Xianfeng Gu},
  url={http://archive.ymsc.tsinghua.edu.cn/pacm_paperurl/20160905174730227281629},
  booktitle={IEEE Conference on Computer Visions and Pattern Recognition},
  pages={4169-4176},
  year={2014},
}
Wei Zeng, Ronald Lok Ming Lui, and Xianfeng Gu. Surface Registration by Optimization in Constrained Diffeomorphism Space. 2014. In IEEE Conference on Computer Visions and Pattern Recognition. pp.4169-4176. http://archive.ymsc.tsinghua.edu.cn/pacm_paperurl/20160905174730227281629.
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